{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}R:\WSV2\TBu_BMa\Subsidies Project\Plot_F4.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}15 Sep 2023, 10:45:16
{txt}
{com}. set more off
{txt}
{com}. 
. *keep if (energy_label_eu=="A+"|energy_label_eu=="A+++"|energy_label_eu=="A++")
. 
. 
. by id country, sort: egen firstyear=min(year)
{txt}
{com}. 
. encode country,gen(icountry)
{txt}
{com}. 
. /*
> drop if units==.
> drop if units==0
> by id country firstyear, sort: egen firstmonth=min(month) if firstyear==year
> tab firstmonth
> */
. 
. ********************************************************************************
. 
. preserve
{txt}
{com}. 
. **Austria, refrigerators and freezers, diffusion of energy class A++ 
. 
. sort date country
{txt}
{com}. 
. **program starts 2009 September, graph can start 2006, include products introduced 2005 or later, focus on years starting 2006
. 
. by date country, sort: egen sumunits_e=sum(units)        if (category=="refrigerator"|category=="freezer") & energy_label_eu=="A++" 
{txt}(3,680,822 missing values generated)

{com}. by date country, sort: egen sumunits_a=sum(units)    if (category=="refrigerator"|category=="freezer")                          
{txt}(1,341,862 missing values generated)

{com}. 
. gen ratio=sumunits_e/sumunits_a
{txt}(3,680,822 missing values generated)

{com}. 
. collapse (mean) ratio year month icountry, by(date country)
{res}{txt}
{com}. 
. regress ratio i.icountry if (year<=2008| (year==2009 & month<9)) & (year >=2007 | (year==2006 & month>=9))

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       268
{txt}{hline 13}{c +}{hline 34}   F(7, 260)       = {res}    75.85
{txt}       Model {c |} {res}  .28386725         7  .040552464   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} .139005999       260  .000534638   {txt}R-squared       ={res}    0.6713
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.6624
{txt}       Total {c |} {res} .422873248       267  .001583795   {txt}Root MSE        =   {res} .02312

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       ratio{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}icountry {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-.0599121{col 26}{space 2} .0056177{col 37}{space 1}  -10.66{col 46}{space 3}0.000{col 54}{space 4}-.0709741{col 67}{space 3}-.0488501
{txt}{space 10}3  {c |}{col 14}{res}{space 2}-.0459376{col 26}{space 2}   .00545{col 37}{space 1}   -8.43{col 46}{space 3}0.000{col 54}{space 4}-.0566693{col 67}{space 3}-.0352059
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0299217{col 26}{space 2}   .00545{col 37}{space 1}    5.49{col 46}{space 3}0.000{col 54}{space 4}   .01919{col 67}{space 3} .0406533
{txt}{space 10}5  {c |}{col 14}{res}{space 2}-.0592506{col 26}{space 2}   .00545{col 37}{space 1}  -10.87{col 46}{space 3}0.000{col 54}{space 4}-.0699823{col 67}{space 3}-.0485189
{txt}{space 10}6  {c |}{col 14}{res}{space 2}-.0570326{col 26}{space 2}   .00545{col 37}{space 1}  -10.46{col 46}{space 3}0.000{col 54}{space 4}-.0677643{col 67}{space 3}-.0463009
{txt}{space 10}7  {c |}{col 14}{res}{space 2}-.0603974{col 26}{space 2} .0064485{col 37}{space 1}   -9.37{col 46}{space 3}0.000{col 54}{space 4}-.0730953{col 67}{space 3}-.0476994
{txt}{space 10}8  {c |}{col 14}{res}{space 2}-.0540687{col 26}{space 2}   .00545{col 37}{space 1}   -9.92{col 46}{space 3}0.000{col 54}{space 4}-.0648004{col 67}{space 3} -.043337
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} .0605664{col 26}{space 2} .0038537{col 37}{space 1}   15.72{col 46}{space 3}0.000{col 54}{space 4} .0529779{col 67}{space 3} .0681548
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. predict ratio_within, resid
{txt}(24 missing values generated)

{com}. browse date icountry year month ratio ratio_within
{txt}
{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if country=="Austria"
{txt}(157 real changes made)

{com}. collapse (mean) ratio_within year month, by(date treat)
{res}{txt}
{com}. 
. twoway scatter ratio_within date if (year >=2007 | (year==2006 & month>=9)) & year <=2010 & treat==1, connect(l)  msize(small) msymbol(Oh) mcolor(black) lcolor(black)||scatter ratio_within date if (year >=2007 | (year==2006 & month>=9)) & year <=2010 & treat==0, connect(l)  msize(small) msymbol(Th) mcolor(sienna) lcolor(sienna) title("") ytitle("Market Share of A++ Refrigerators & Freezers")graphregion(color(white)) tline(2009m9, lcolor(gray) lpattern(longdash)) tline(2010m9, lcolor(gray) lpattern(longdash))  xtitle("") legend(lab (1 "Austria") lab (2 "All excl. Austria"))
{res}{txt}
{com}. 
. graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_AT1_36.eps", as(eps) fontface("Times New Roman") replace
{txt}{p 0 4 2}
file {bf}
R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_AT1_36.eps{rm}
saved as
EPS
format
{p_end}

{com}. *graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_AT1.png", as(png) replace
. 
. restore
{txt}
{com}. 
. 
. ********************************************************************************
. 
. preserve
{txt}
{com}. 
. **Austria, washing machines, diffusion of energy class A++ 
. 
. sort date country
{txt}
{com}. 
. **program starts 2010 April, graph can start 2007, include products introduced 2005 or later, focus on years starting 2006
. 
. by date country, sort: egen sumunits_e=sum(units)        if (category=="washing machine") & energy_label_eu=="A++" 
{txt}(4,074,551 missing values generated)

{com}. by date country, sort: egen sumunits_a=sum(units)    if (category=="washing machine")                          
{txt}(2,848,241 missing values generated)

{com}. 
. gen ratio=sumunits_e/sumunits_a
{txt}(4,074,551 missing values generated)

{com}. 
. collapse (mean) ratio year month icountry, by(date country)
{res}{txt}
{com}. 
. regress ratio i.icountry if (year<=2009| (year==2010 & month<4)) & (year >=2007 | (year==2006 & month>=4))

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       354
{txt}{hline 13}{c +}{hline 34}   F(7, 346)       = {res}    57.91
{txt}       Model {c |} {res} .092509332         7  .013215619   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} .078954161       346  .000228191   {txt}R-squared       ={res}    0.5395
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.5302
{txt}       Total {c |} {res} .171463493       353  .000485732   {txt}Root MSE        =   {res} .01511

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       ratio{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}icountry {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-.0222515{col 26}{space 2} .0030835{col 37}{space 1}   -7.22{col 46}{space 3}0.000{col 54}{space 4}-.0283163{col 67}{space 3}-.0161868
{txt}{space 10}3  {c |}{col 14}{res}{space 2}-.0177179{col 26}{space 2} .0030835{col 37}{space 1}   -5.75{col 46}{space 3}0.000{col 54}{space 4}-.0237826{col 67}{space 3}-.0116531
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0249057{col 26}{space 2} .0030835{col 37}{space 1}    8.08{col 46}{space 3}0.000{col 54}{space 4} .0188409{col 67}{space 3} .0309704
{txt}{space 10}5  {c |}{col 14}{res}{space 2}-.0225281{col 26}{space 2} .0030835{col 37}{space 1}   -7.31{col 46}{space 3}0.000{col 54}{space 4}-.0285929{col 67}{space 3}-.0164633
{txt}{space 10}6  {c |}{col 14}{res}{space 2}-.0181342{col 26}{space 2} .0030835{col 37}{space 1}   -5.88{col 46}{space 3}0.000{col 54}{space 4}-.0241989{col 67}{space 3}-.0120694
{txt}{space 10}7  {c |}{col 14}{res}{space 2}-.0250822{col 26}{space 2} .0036339{col 37}{space 1}   -6.90{col 46}{space 3}0.000{col 54}{space 4}-.0322296{col 67}{space 3}-.0179348
{txt}{space 10}8  {c |}{col 14}{res}{space 2}-.0190268{col 26}{space 2} .0032565{col 37}{space 1}   -5.84{col 46}{space 3}0.000{col 54}{space 4}-.0254319{col 67}{space 3}-.0126217
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} .0258691{col 26}{space 2} .0021804{col 37}{space 1}   11.86{col 46}{space 3}0.000{col 54}{space 4} .0215806{col 67}{space 3} .0301575
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. predict ratio_within, resid
{txt}(108 missing values generated)

{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if country=="Austria"
{txt}(157 real changes made)

{com}. collapse (mean) ratio_within year month, by(date treat)
{res}{txt}
{com}. 
. twoway scatter ratio_within date if (year >=2007 | (year==2006 & month>=4)) & year <=2011 & treat==1, connect(l)  msize(small) msymbol(Oh) mcolor(black) lcolor(black)||scatter ratio_within date if (year >=2007 | (year==2006 & month>=4)) & year <=2011 & treat==0, connect(l)  msize(small) msymbol(Th) mcolor(sienna) lcolor(sienna) title("") ytitle("Market Share of A++ Washing Machines")graphregion(color(white)) tline(2010m4, lcolor(gray) lpattern(longdash))  xtitle("") legend(lab (1 "Austria") lab (2 "All excl. Austria"))
{res}{txt}
{com}. 
. graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_AT2_36.eps", as(eps) fontface("Times New Roman") replace
{txt}{p 0 4 2}
file {bf}
R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_AT2_36.eps{rm}
saved as
EPS
format
{p_end}

{com}. *graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_AT1.png", as(png) replace
. 
. restore
{txt}
{com}. 
. ********************************************************************************
. 
. preserve
{txt}
{com}. 
. **Hungary, refrigerators and freezers, diffusion of energy class A++ and A+++
. 
. sort date country
{txt}
{com}. 
. **second program starts 2016 September, due to earlier program graph can start 2013, include products introduced 2011 or later, focus on years starting 2012
. 
. by date country, sort: egen sumunits_e=sum(units)        if (category=="refrigerator"|category=="freezer")  & (energy_label_eu=="A++"|energy_label_eu=="A+++")  
{txt}(3,593,973 missing values generated)

{com}. by date country, sort: egen sumunits_a=sum(units)    if (category=="refrigerator"|category=="freezer")                                                     
{txt}(1,341,862 missing values generated)

{com}. 
. gen ratio=sumunits_e/sumunits_a
{txt}(3,593,973 missing values generated)

{com}. 
. collapse (mean) ratio year month icountry, by(date country)
{res}{txt}
{com}. 
. regress ratio i.icountry if (year<=2015 | (year==2016 & month < 9)) & (year >=2014 | (year==2013 & month>=9))

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       288
{txt}{hline 13}{c +}{hline 34}   F(7, 280)       = {res}   876.33
{txt}       Model {c |} {res} 11.5536553         7  1.65052218   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} .527363661       280  .001883442   {txt}R-squared       ={res}    0.9563
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9553
{txt}       Total {c |} {res} 12.0810189       287  .042094143   {txt}Root MSE        =   {res}  .0434

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       ratio{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}icountry {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-.4265407{col 26}{space 2} .0102292{col 37}{space 1}  -41.70{col 46}{space 3}0.000{col 54}{space 4}-.4466765{col 67}{space 3}-.4064049
{txt}{space 10}3  {c |}{col 14}{res}{space 2}-.1404545{col 26}{space 2} .0102292{col 37}{space 1}  -13.73{col 46}{space 3}0.000{col 54}{space 4}-.1605903{col 67}{space 3}-.1203186
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0888282{col 26}{space 2} .0102292{col 37}{space 1}    8.68{col 46}{space 3}0.000{col 54}{space 4} .0686923{col 67}{space 3}  .108964
{txt}{space 10}5  {c |}{col 14}{res}{space 2} -.370762{col 26}{space 2} .0102292{col 37}{space 1}  -36.25{col 46}{space 3}0.000{col 54}{space 4}-.3908978{col 67}{space 3}-.3506261
{txt}{space 10}6  {c |}{col 14}{res}{space 2}-.3438128{col 26}{space 2} .0102292{col 37}{space 1}  -33.61{col 46}{space 3}0.000{col 54}{space 4}-.3639487{col 67}{space 3} -.323677
{txt}{space 10}7  {c |}{col 14}{res}{space 2} -.502798{col 26}{space 2} .0102292{col 37}{space 1}  -49.15{col 46}{space 3}0.000{col 54}{space 4}-.5229338{col 67}{space 3}-.4826621
{txt}{space 10}8  {c |}{col 14}{res}{space 2}-.3668731{col 26}{space 2} .0102292{col 37}{space 1}  -35.87{col 46}{space 3}0.000{col 54}{space 4}-.3870089{col 67}{space 3}-.3467373
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2}  .549627{col 26}{space 2} .0072331{col 37}{space 1}   75.99{col 46}{space 3}0.000{col 54}{space 4} .5353889{col 67}{space 3} .5638652
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. predict ratio_within, resid
{txt}(24 missing values generated)

{com}. 
. drop if country=="Croatia"
{txt}(157 observations deleted)

{com}. gen treat=0
{txt}
{com}. replace treat=1 if country=="Hungary"
{txt}(157 real changes made)

{com}. collapse (mean) ratio_within year month, by(date treat)
{res}{txt}
{com}. 
. twoway scatter ratio_within date if (year >=2014 | (year==2013 & month>=9)) & year <=2018 & treat==1, connect(l)  msize(small) msymbol(Oh) mcolor(black) lcolor(black)||scatter ratio_within date if year<=2018 & (year >=2014 | (year==2013 & month>=9)) & treat==0, connect(l)  msize(small) msymbol(Th) mcolor(sienna) lcolor(sienna) title("") ytitle("Market Share of  A++ & A+++ Refrigerators & Freezers")graphregion(color(white)) tline(2015m2, lcolor(gray) lpattern(longdash)) tline(2016m9, lcolor(gray) lpattern(longdash))  xtitle("") legend(lab (1 "Hungary") lab (2 "All excl. Hungary & Croatia"))
{res}{txt}
{com}. 
. graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU1_36.eps", as(eps) fontface("Times New Roman") replace
{txt}{p 0 4 2}
file {bf}
R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU1_36.eps{rm}
saved as
EPS
format
{p_end}

{com}. *graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU1.png", as(png)  replace
. 
. restore
{txt}
{com}. 
. 
. 
. preserve
{txt}
{com}. 
. **Hungary, refrigerators and freezers, diffusion of energy class A+ 
. 
. sort date country
{txt}
{com}. 
. by date country, sort: egen sumunits_e=sum(units)        if (category=="refrigerator"|category=="freezer")  & (energy_label_eu=="A+")                           
{txt}(3,119,286 missing values generated)

{com}. by date country, sort: egen sumunits_a=sum(units)    if (category=="refrigerator"|category=="freezer")                                                     
{txt}(1,341,862 missing values generated)

{com}. 
. gen ratio=sumunits_e/sumunits_a
{txt}(3,119,286 missing values generated)

{com}. 
. collapse (mean) ratio year month icountry, by(date country)
{res}{txt}
{com}. 
. regress ratio i.icountry if (year<=2015 | (year==2016 & month < 9)) & (year >=2014 | (year==2013 & month>=9))

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       288
{txt}{hline 13}{c +}{hline 34}   F(7, 280)       = {res}   622.50
{txt}       Model {c |} {res} 9.10334462         7   1.3004778   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} .584952794       280  .002089117   {txt}R-squared       ={res}    0.9396
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.9381
{txt}       Total {c |} {res} 9.68829741       287  .033757134   {txt}Root MSE        =   {res} .04571

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       ratio{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}icountry {c |}
{space 10}2  {c |}{col 14}{res}{space 2} .3753458{col 26}{space 2} .0107732{col 37}{space 1}   34.84{col 46}{space 3}0.000{col 54}{space 4}  .354139{col 67}{space 3} .3965525
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .1375845{col 26}{space 2} .0107732{col 37}{space 1}   12.77{col 46}{space 3}0.000{col 54}{space 4} .1163777{col 67}{space 3} .1587912
{txt}{space 10}4  {c |}{col 14}{res}{space 2}-.0817879{col 26}{space 2} .0107732{col 37}{space 1}   -7.59{col 46}{space 3}0.000{col 54}{space 4}-.1029947{col 67}{space 3}-.0605812
{txt}{space 10}5  {c |}{col 14}{res}{space 2}  .359356{col 26}{space 2} .0107732{col 37}{space 1}   33.36{col 46}{space 3}0.000{col 54}{space 4} .3381492{col 67}{space 3} .3805627
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .3212762{col 26}{space 2} .0107732{col 37}{space 1}   29.82{col 46}{space 3}0.000{col 54}{space 4} .3000695{col 67}{space 3}  .342483
{txt}{space 10}7  {c |}{col 14}{res}{space 2} .0194051{col 26}{space 2} .0107732{col 37}{space 1}    1.80{col 46}{space 3}0.073{col 54}{space 4}-.0018016{col 67}{space 3} .0406119
{txt}{space 10}8  {c |}{col 14}{res}{space 2}  .365645{col 26}{space 2} .0107732{col 37}{space 1}   33.94{col 46}{space 3}0.000{col 54}{space 4} .3444383{col 67}{space 3} .3868518
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} .4372719{col 26}{space 2} .0076178{col 37}{space 1}   57.40{col 46}{space 3}0.000{col 54}{space 4} .4222765{col 67}{space 3} .4522674
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. predict ratio_within, resid
{txt}
{com}. 
. drop if country=="Croatia"
{txt}(157 observations deleted)

{com}. gen treat=0
{txt}
{com}. replace treat=1 if country=="Hungary"
{txt}(157 real changes made)

{com}. collapse (mean) ratio_within year month, by(date treat)
{res}{txt}
{com}. 
. twoway scatter ratio_within date if (year >=2014 | (year==2013 & month>=9)) & year <=2018 & treat==1, connect(l)  msize(small) msymbol(Oh) mcolor(black) lcolor(black)||scatter ratio_within date if (year >=2014 | (year==2013 & month>=9)) & year <=2018 & treat==0, connect(l)  msize(small) msymbol(Th) mcolor(sienna) lcolor(sienna) title("") ytitle("Market Share of  A+ Refrigerators & Freezers")graphregion(color(white)) tline(2015m2, lcolor(gray) lpattern(longdash)) tline(2016m9, lcolor(gray) lpattern(longdash))  xtitle("") legend(lab (1 "Hungary") lab (2 "All excl. Hungary & Croatia"))
{res}{txt}
{com}. 
. graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU2_36.eps", as(eps) fontface("Times New Roman") replace
{txt}{p 0 4 2}
file {bf}
R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU2_36.eps{rm}
saved as
EPS
format
{p_end}

{com}. *graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU2.png", as(png) replace
. 
. restore
{txt}
{com}. 
. ********************************************************************************
. 
. preserve
{txt}
{com}. 
. **Hungary, washing machines, diffusion of energy class A+++
. 
. sort date country
{txt}
{com}. 
. **program starts 2015 October, include products introduced 2011 or later, focus on years starting 2012
. 
. by date country, sort: egen sumunits_e=sum(units)        if (category=="washing machine") & (energy_label_eu=="A+++")    
{txt}(3,915,223 missing values generated)

{com}. by date country, sort: egen sumunits_a=sum(units)    if (category=="washing machine")                               
{txt}(2,848,241 missing values generated)

{com}. 
. gen ratio=sumunits_e/sumunits_a
{txt}(3,915,223 missing values generated)

{com}. 
. collapse (mean) ratio year month icountry, by(date country)
{res}{txt}
{com}. 
. regress ratio i.icountry if (year<=2014 | (year==2015 & month < 10)) & (year >=2013 | (year==2012 & month>=10))

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       288
{txt}{hline 13}{c +}{hline 34}   F(7, 280)       = {res}    85.13
{txt}       Model {c |} {res} 6.61262647         7  .944660925   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 3.10693079       280  .011096181   {txt}R-squared       ={res}    0.6803
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.6724
{txt}       Total {c |} {res} 9.71955726       287  .033866053   {txt}Root MSE        =   {res} .10534

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       ratio{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}icountry {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-.2480945{col 26}{space 2} .0248285{col 37}{space 1}   -9.99{col 46}{space 3}0.000{col 54}{space 4}-.2969687{col 67}{space 3}-.1992203
{txt}{space 10}3  {c |}{col 14}{res}{space 2}-.1353336{col 26}{space 2} .0248285{col 37}{space 1}   -5.45{col 46}{space 3}0.000{col 54}{space 4}-.1842078{col 67}{space 3}-.0864594
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .1353112{col 26}{space 2} .0248285{col 37}{space 1}    5.45{col 46}{space 3}0.000{col 54}{space 4} .0864369{col 67}{space 3} .1841854
{txt}{space 10}5  {c |}{col 14}{res}{space 2}-.3363008{col 26}{space 2} .0248285{col 37}{space 1}  -13.54{col 46}{space 3}0.000{col 54}{space 4}-.3851751{col 67}{space 3}-.2874266
{txt}{space 10}6  {c |}{col 14}{res}{space 2}-.2317239{col 26}{space 2} .0248285{col 37}{space 1}   -9.33{col 46}{space 3}0.000{col 54}{space 4}-.2805981{col 67}{space 3}-.1828497
{txt}{space 10}7  {c |}{col 14}{res}{space 2}-.3169382{col 26}{space 2} .0248285{col 37}{space 1}  -12.77{col 46}{space 3}0.000{col 54}{space 4}-.3658124{col 67}{space 3}-.2680639
{txt}{space 10}8  {c |}{col 14}{res}{space 2}-.1181178{col 26}{space 2} .0248285{col 37}{space 1}   -4.76{col 46}{space 3}0.000{col 54}{space 4} -.166992{col 67}{space 3}-.0692436
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} .5189418{col 26}{space 2} .0175564{col 37}{space 1}   29.56{col 46}{space 3}0.000{col 54}{space 4} .4843825{col 67}{space 3} .5535011
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. predict ratio_within, resid
{txt}(48 missing values generated)

{com}. 
. drop if country=="Croatia"
{txt}(157 observations deleted)

{com}. gen treat=0
{txt}
{com}. replace treat=1 if country=="Hungary"
{txt}(157 real changes made)

{com}. collapse (mean) ratio_within year month, by(date treat)
{res}{txt}
{com}. 
. twoway scatter ratio_within date if (year >=2013 | (year==2012 & month>=10)) & treat==1, connect(l)  msize(small) msymbol(Oh) mcolor(black) lcolor(black)||scatter ratio_within date if (year >=2013 | (year==2012 & month>=10)) & treat==0 ,connect(l)  msize(small) msymbol(Th) mcolor(sienna) lcolor(sienna) title("") ytitle("Market Share of A+++ Washing Machines")graphregion(color(white)) tline(2015m10, lcolor(gray) lpattern(longdash))   xtitle("") legend(lab (1 "Hungary") lab (2 "All excl. Hungary & Croatia"))
{res}{txt}
{com}. 
. graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU3_36.eps", as(eps) fontface("Times New Roman") replace
{txt}{p 0 4 2}
file {bf}
R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU3_36.eps{rm}
saved as
EPS
format
{p_end}

{com}. *graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU3.png", as(png) replace
. 
. restore
{txt}
{com}. 
. ********************************************************************************
. 
. preserve
{txt}
{com}. 
. **Hungary, washing machines, diffusion of energy class A+ & A++
. 
. sort date country
{txt}
{com}. 
. **program starts 2015 October, include products introduced 2011 or later, focus on years starting 2012
. 
. by date country, sort: egen sumunits_e=sum(units)     if (category=="washing machine") & (energy_label_eu=="A+"|energy_label_eu=="A++")  
{txt}(3,888,436 missing values generated)

{com}. by date country, sort: egen sumunits_a=sum(units)     if (category=="washing machine")                                                  
{txt}(2,848,241 missing values generated)

{com}. 
. gen ratio=sumunits_e/sumunits_a
{txt}(3,888,436 missing values generated)

{com}. 
. collapse (mean) ratio year month icountry, by(date country)
{res}{txt}
{com}. 
. regress ratio i.icountry if (year<=2014 | (year==2015 & month < 10)) & (year >=2013 | (year==2012 & month>=10))

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       288
{txt}{hline 13}{c +}{hline 34}   F(7, 280)       = {res}   129.97
{txt}       Model {c |} {res} 5.60014741         7  .800021059   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 1.72349778       280  .006155349   {txt}R-squared       ={res}    0.7647
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.7588
{txt}       Total {c |} {res} 7.32364519       287  .025517928   {txt}Root MSE        =   {res} .07846

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       ratio{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}icountry {c |}
{space 10}2  {c |}{col 14}{res}{space 2} .2103315{col 26}{space 2} .0184923{col 37}{space 1}   11.37{col 46}{space 3}0.000{col 54}{space 4}   .17393{col 67}{space 3}  .246733
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .2016665{col 26}{space 2} .0184923{col 37}{space 1}   10.91{col 46}{space 3}0.000{col 54}{space 4}  .165265{col 67}{space 3}  .238068
{txt}{space 10}4  {c |}{col 14}{res}{space 2}-.0805634{col 26}{space 2} .0184923{col 37}{space 1}   -4.36{col 46}{space 3}0.000{col 54}{space 4}-.1169649{col 67}{space 3}-.0441619
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .3943299{col 26}{space 2} .0184923{col 37}{space 1}   21.32{col 46}{space 3}0.000{col 54}{space 4} .3579283{col 67}{space 3} .4307314
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .2540677{col 26}{space 2} .0184923{col 37}{space 1}   13.74{col 46}{space 3}0.000{col 54}{space 4} .2176662{col 67}{space 3} .2904693
{txt}{space 10}7  {c |}{col 14}{res}{space 2} .2290484{col 26}{space 2} .0184923{col 37}{space 1}   12.39{col 46}{space 3}0.000{col 54}{space 4} .1926469{col 67}{space 3}   .26545
{txt}{space 10}8  {c |}{col 14}{res}{space 2} .1507579{col 26}{space 2} .0184923{col 37}{space 1}    8.15{col 46}{space 3}0.000{col 54}{space 4} .1143564{col 67}{space 3} .1871594
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} .3651095{col 26}{space 2}  .013076{col 37}{space 1}   27.92{col 46}{space 3}0.000{col 54}{space 4} .3393698{col 67}{space 3} .3908493
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. predict ratio_within, resid
{txt}(12 missing values generated)

{com}. 
. drop if country=="Croatia"
{txt}(157 observations deleted)

{com}. gen treat=0
{txt}
{com}. replace treat=1 if country=="Hungary"
{txt}(157 real changes made)

{com}. collapse (mean) ratio_within year month, by(date treat)
{res}{txt}
{com}. 
. twoway scatter ratio_within date if (year >=2013 | (year==2012 & month>=10)) & treat==1, connect(l)  msize(small) msymbol(Oh) mcolor(black) lcolor(black)||scatter ratio_within date if (year >=2013 | (year==2012 & month>=10)) & treat==0 ,connect(l)  msize(small) msymbol(Th) mcolor(sienna) lcolor(sienna) title("") ytitle("Market Share of A+ and A++ Washing Machines")graphregion(color(white)) tline(2015m10, lcolor(gray) lpattern(longdash))   xtitle("") legend(lab (1 "Hungary") lab (2 "All excl. Hungary & Croatia"))
{res}{txt}
{com}. 
. graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU4_36.eps", as(eps) fontface("Times New Roman") replace
{txt}{p 0 4 2}
file {bf}
R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU4_36.eps{rm}
saved as
EPS
format
{p_end}

{com}. *graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HU4.png", as(png) replace
. 
. restore
{txt}
{com}. 
. ********************************************************************************
. 
. preserve
{txt}
{com}. 
. **Croatia, washing machines, diffusion of energy class A+++
. 
. sort date country
{txt}
{com}. 
. **program starts 2015 June, include products introduced 2011 or later, focus on years starting 2012
. 
. by date country, sort: egen sumunits_e=sum(units)        if (category=="washing machine") & (energy_label_eu=="A+++")  
{txt}(3,915,223 missing values generated)

{com}. by date country, sort: egen sumunits_a=sum(units)    if (category=="washing machine")                             
{txt}(2,848,241 missing values generated)

{com}. 
. gen ratio=sumunits_e/sumunits_a
{txt}(3,915,223 missing values generated)

{com}. 
. collapse (mean) ratio year month icountry, by(date country)
{res}{txt}
{com}. 
. regress ratio i.icountry if (year<=2014 | (year==2015 & month < 6)) & (year >=2013 | (year==2012 & month>=6))

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       288
{txt}{hline 13}{c +}{hline 34}   F(7, 280)       = {res}    73.14
{txt}       Model {c |} {res} 6.13645348         7  .876636212   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 3.35608669       280  .011986024   {txt}R-squared       ={res}    0.6465
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.6376
{txt}       Total {c |} {res} 9.49254017       287  .033075053   {txt}Root MSE        =   {res} .10948

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       ratio{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}icountry {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-.2401958{col 26}{space 2} .0258048{col 37}{space 1}   -9.31{col 46}{space 3}0.000{col 54}{space 4}-.2909919{col 67}{space 3}-.1893997
{txt}{space 10}3  {c |}{col 14}{res}{space 2} -.134672{col 26}{space 2} .0258048{col 37}{space 1}   -5.22{col 46}{space 3}0.000{col 54}{space 4}-.1854681{col 67}{space 3}-.0838758
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .1387025{col 26}{space 2} .0258048{col 37}{space 1}    5.38{col 46}{space 3}0.000{col 54}{space 4} .0879063{col 67}{space 3} .1894986
{txt}{space 10}5  {c |}{col 14}{res}{space 2}-.3201652{col 26}{space 2} .0258048{col 37}{space 1}  -12.41{col 46}{space 3}0.000{col 54}{space 4}-.3709613{col 67}{space 3} -.269369
{txt}{space 10}6  {c |}{col 14}{res}{space 2}-.2263773{col 26}{space 2} .0258048{col 37}{space 1}   -8.77{col 46}{space 3}0.000{col 54}{space 4}-.2771735{col 67}{space 3}-.1755812
{txt}{space 10}7  {c |}{col 14}{res}{space 2}-.2931368{col 26}{space 2} .0258048{col 37}{space 1}  -11.36{col 46}{space 3}0.000{col 54}{space 4}-.3439329{col 67}{space 3}-.2423407
{txt}{space 10}8  {c |}{col 14}{res}{space 2}-.1189638{col 26}{space 2} .0258048{col 37}{space 1}   -4.61{col 46}{space 3}0.000{col 54}{space 4}-.1697599{col 67}{space 3}-.0681677
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} .4753208{col 26}{space 2} .0182468{col 37}{space 1}   26.05{col 46}{space 3}0.000{col 54}{space 4} .4394026{col 67}{space 3} .5112391
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. predict ratio_within, resid
{txt}(48 missing values generated)

{com}. 
. drop if country=="Hungary"
{txt}(157 observations deleted)

{com}. gen treat=0
{txt}
{com}. replace treat=1 if country=="Croatia"
{txt}(157 real changes made)

{com}. collapse (mean) ratio_within year month, by(date treat)
{res}{txt}
{com}. 
. twoway scatter ratio_within date if (year >=2013 | (year==2012 & month>=3)) & treat==1, connect(l)  msize(small) msymbol(Oh) mcolor(black) lcolor(black)||scatter ratio_within date if (year >=2013 | (year==2012 & month>=3)) & treat==0, connect(l)  msize(small) msymbol(Th) mcolor(sienna) lcolor(sienna) title("") ytitle("Market Share of  A+++  Washing Machines")graphregion(color(white)) tline(2015m6, lcolor(gray) lpattern(longdash)) tline(2015m10, lcolor(gray) lpattern(longdash))  xtitle("") legend(lab (1 "Croatia") lab (2 "All excl. Croatia & Hungary"))
{res}{txt}
{com}. 
. 
. graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HR1_36.eps", as(eps) fontface("Times New Roman") replace
{txt}{p 0 4 2}
file {bf}
R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HR1_36.eps{rm}
saved as
EPS
format
{p_end}

{com}. *graph export "R:\WSV2\TBu_BMa\Subsidies Project\Graphs\Plot_HR1.png", as(png) replace
. 
. restore
{txt}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}R:\WSV2\TBu_BMa\Subsidies Project\Plot_F4.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}15 Sep 2023, 10:47:01
{txt}{.-}
{smcl}
{txt}{sf}{ul off}